import numpy as np
#import keras
#from keras import backend as K
#from keras.models import Sequential, Model, load_model
#from keras.callbacks import TensorBoard
#import tensorflow as tf
import matplotlib.pyplot as plt
import math

x_train = np.load('./ad_train_dat.npy')
y_train = np.load('./pwm_train_label.npy')
x_test = np.load('./ad_test_dat.npy')
y_test = np.load('./pwm_test_label.npy')


plt.figure(figsize=(18,15))

x_test = x_test.reshape(x_test.shape[0], x_test.shape[1], x_test.shape[2],1)

x_train = x_train.reshape(x_train.shape[0], x_train.shape[1],x_train.shape[2],1)
y_test = y_test.reshape(y_test.size,1)
y_train = y_train.reshape(y_train.size, 1)

x_input = x_test
y_input = y_test

x_input = x_input.astype('float32')
y_input = y_input.astype('float32')

x = np.arange(0,y_input.size)

plt.plot(x,y_input, color='y',label='original pwm')
